Automated Matchmaking to Improve Accuracy of Applicant Selection for University Education System
This addresses the issue of student frustration and resource inefficiency in university admissions by minimizing mismatches between students and courses, though it appears incremental as it builds on existing selection approaches.
The study tackled the problem of inaccurate applicant selection in universities by proposing an automated matchmaking method that matches student skills to program requirements, showing it as a viable alternative with empirical comparisons to other methods.
The accurate applicant selection for university education is imperative to ensure fairness and optimal use of institutional resources. Although various approaches are operational in tertiary educational institutions for selecting applicants, a novel method of automated matchmaking is explored in the current study. The method functions by matching a prospective students skills profile to a programmes requisites profile. Empirical comparisons of the results, calculated by automated matchmaking and two other selection methods, show matchmaking to be a viable alternative for accurate selection of applicants. Matchmaking offers a unique advantage that it neither requires data from other applicants nor compares applicants with each other. Instead, it emphasises norms that define admissibility to a programme. We have proposed the use of technology to minimize the gap between students aspirations, skill sets and course requirements. It is a solution to minimize the number of students who get frustrated because of mismatched course selection.